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Field
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in Europe by fueling innovation through research partnerships with industry, boosting R&D investments leading to economic growth, and attracting highly qualified talent. We look for researchers from
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-level data on single cell level, R/Bioconductor and Python/Tensorflow will be useful but is not a requirement. An experimental researcher with an interest in methodologically driven cancer research
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into longitudinal studies and in using functional MRI and scripting-based languages (e.g. Matlab, R, Python). They must also have experience of conducting research with human participants and of performing highly
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experience with programming tools such as R or Python. An interest in acquiring new data science and programming skills is required. A keen interest in teaching and academic development. An excellent academic
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experience of data science analytical packages and R or Python would be advantageous. Funding The project is funded by the UKHSA and Nottingham University Business School. As a UK public body, UKHSA can only
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, and skills in modelling & programming tools such as SINCAL, PowerFactory, OpenDSS, PSCAD, Python, Matlab, R, or Julia would be desirable. For full details about this role, please review the Position
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(e.g. Julia, Python, R) are a requirement Good programming skills in a low level language (e.g. C/C++, Fortran) will be considered advantageous Our offer A vibrant research community in an open, diverse
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Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Previous relevant research experience Publications Programming skills (R or Python
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Strong publication record A keen and documented interest in the research agenda of the project Experience with analysis of longitudinal data and related data management Proficiency in using Stata and/or R
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demonstrate experience in or interest in working with R/Python. You can demonstrate very good writing skills. You can demonstrate a proactive attitude. You have good communication skills, and a collaborative